1. Trains: 2 data formats (structured, one-instance-per-line)
2. Pittsburgh Bridges: Bridges database that has original and numeric-discretized datasets
3. Tennis Major Tournament Match Statistics: This is a collection of 8 files containing the match statistics for both women and men at the four major tennis tournaments of the year 2013. Each file has 42 columns and a minimum of 76 rows.
4. Flags: From Collins Gem Guide to Flags, 1986
5. Automobile: From 1985 Ward's Automotive Yearbook
6. University: Data in original (LISP-readable) form
7. Libras Movement: The data set contains 15 classes of 24 instances each. Each class references to a hand movement type in LIBRAS (Portuguese
name 'LÍngua BRAsileira de Sinais', oficial brazilian signal language).
8. Chronic_Kidney_Disease: This dataset can be used to predict the chronic kidney disease and it can be collected from the hospital nearly 2 months of period.
9. Housing: Taken from StatLib library
10. Meta-data: Meta-Data was used in order to give advice about which classification method is appropriate for a particular dataset (taken from results of Statlog project).
11. Folio: 20 photos of leaves for each of 32 different species.
12. Japanese Vowels: This dataset records 640 time series of 12 LPC cepstrum coefficients taken from nine male speakers.
13. Statlog (Vehicle Silhouettes): 3D objects within a 2D image by application of an ensemble of shape feature extractors to the 2D silhouettes of the objects.
14. QSAR biodegradation: Data set containing values for 41 attributes (molecular descriptors) used to classify 1055 chemicals into 2 classes (ready and not ready biodegradable).
15. Geographical Original of Music: Instances in this dataset contain audio features extracted from 1059 wave files. The task associated with the data is to predict the geographical origin of music.
16. Image Segmentation: Image data described by high-level numeric-valued attributes, 7 classes
17. Statlog (Image Segmentation): This dataset is an image segmentation database similar to a database already present in the repository (Image segmentation database) but in a slightly different form.
18. Australian Sign Language signs (High Quality): This data consists of sample of Auslan (Australian Sign Language) signs. 27 examples of each of 95 Auslan signs were captured from a native signer using high-quality position trackers
19. seismic-bumps: The data describe the problem of high energy (higher than 10^4 J) seismic bumps forecasting in a coal
mine. Data come from two of longwalls located in a Polish coal mine.
20. Turkiye Student Evaluation: This data set contains a total 5820 evaluation scores provided by students from Gazi University in Ankara (Turkey). There is a total of 28 course specific questions and additional 5 attributes.
21. Australian Sign Language signs: This data consists of sample of Auslan (Australian Sign Language) signs. Examples of 95 signs were collected from five signers with a total of 6650 sign samples.
22. Spoken Arabic Digit: This dataset contains timeseries of mel-frequency cepstrum coefficients (MFCCs) corresponding to spoken Arabic digits. Includes data from 44 male and 44 female native Arabic speakers.
23. Gesture Phase Segmentation: The dataset is composed by features extracted from 7 videos with people gesticulating, aiming at studying Gesture Phase Segmentation. It contains 50 attributes divided into two files for each video.
24. Firm-Teacher_Clave-Direction_Classification: The data are binary attack-point vectors and their clave-direction class(es) according to the partido-alto-based paradigm.
25. Corel Image Features: This dataset contains image features extracted from a Corel image collection. Four sets of features are available based on the color histogram, color histogram layout, color moments, and co-occurence
26. YearPredictionMSD: Prediction of the release year of a song from audio features. Songs are mostly western, commercial tracks ranging from 1922 to 2011, with a peak in the year 2000s.
27. Record Linkage Comparison Patterns: Element-wise comparison of records with personal data from a record linkage setting. The task is to decide from a comparison pattern whether the underlying records belong to one person.